Staff Data Engineer, Analytics Data Engineering

Staff Data Engineer, Analytics Data Engineering

Join Dropbox's Analytics Data Engineering (ADE) team as a Staff Data Engineer, playing a pivotal role in a Virtual First company. This position is authorized for candidates in Alberta, British Columbia, Ontario, and Saskatchewan, Canada.

About the Role

This is an exciting opportunity to tackle cross-cutting data challenges and drive standardization within Dropbox's analytics ecosystem. You will be instrumental in modernizing our analytics platform, upgrading orchestration infrastructure, and establishing shared, reusable data models with conformed dimensions. The role also involves building a certified metrics framework and laying the groundwork for AI-native data development. You will collaborate closely with Data Science, Data Infrastructure, Product Engineering, and Business Intelligence teams, gaining significant exposure to senior leadership and influencing the technical direction of analytics at Dropbox.

Key Responsibilities

• Lead the design and implementation of shared, reusable data models, defining fact tables, conformed dimensions, and a semantic/metrics layer to ensure a single source of truth.
• Drive standardization of data engineering practices across ADE and functional analytics teams, encompassing pipeline patterns, CI/CD workflows, naming conventions, and data modeling standards.
• Partner with Data Infrastructure to modernize orchestration, enhance pipeline decomposition, and create secure dev/test environments with production data access.
• Architect and implement a shift-left data governance strategy by working with upstream data producers to establish data contracts, SLOs, and code-enforced quality gates.
• Collaborate with Data Science leads and Product Management to translate metric definitions into reliable, certified data pipelines for executive dashboards, WBR reporting, and growth measurement.
• Reduce operational burden through improved pipeline granularity, observability, and failure recovery, establishing robust runbooks and alerting standards.
• Evaluate and integrate AI-native tooling into the data development lifecycle, enabling conversational data exploration and AI-assisted pipeline development.

Note: Many teams at Dropbox run services with on-call rotations. Participation in these rotations is an expectation for engineers on such teams.

Required Qualifications

• BS degree in Computer Science or a related technical field, or equivalent technical experience.
• 12+ years of experience in data engineering or analytics engineering with increasing scope and technical leadership.
• 12+ years of SQL experience, including complex analytical queries, window functions, and performance optimization at scale (Spark SQL).
• 8+ years of Python development experience, including building and maintaining production data pipelines.
• Deep expertise in dimensional data modeling, schema design, and scalable data architecture, with hands-on experience building shared data models across multiple business domains.
• Strong experience with orchestration tools (Airflow strongly preferred) and dbt, including pipeline design, scheduling strategies, and failure recovery patterns.
• Demonstrated ability to drive cross-team technical alignment, establish standards, influence without authority, and collaborate across various engineering and data teams.

Preferred Qualifications

• Experience with Databricks (Unity Catalog, Delta Lake) and modern lakehouse architectures.
• Experience leading orchestration or platform modernization efforts at scale.
• Familiarity with data governance and observability tools such as Atlan, Monte Carlo, Great Expectations, or similar.
• Experience building or contributing to a metrics/semantic layer (dbt MetricFlow, Databricks Metric Views, or equivalent).
• Track record of establishing data engineering standards and best practices in a federated analytics organization.

Compensation & Benefits

The annual salary/OTE for this role in Canada ranges from $204,000 to $276,000 CAD. Dropbox offers a comprehensive total rewards package, including a corporate bonus program or sales incentive, and stock in the form of Restricted Stock Units (RSUs). Detailed benefits information is available online.

About Dropbox

Dropbox is a Virtual First company, serving as a living lab for an enlightened way of working. It fosters a global community of visionaries and doers, shaping the future of work. The Virtual First model combines remote autonomy with intentional in-person connections, promoting deep focus, nonlinear schedules, and asynchronous communication. Employees are encouraged to think critically, stay curious, and leverage modern tools, including AI, to enhance productivity and make work more intuitive, joyful, and human for hundreds of millions worldwide.

Our Engineering Team

The Dropbox Engineering Team develops the technology, platforms, and products that create more enlightened ways of working. They manage a robust systems software layer storing exabytes of data, alongside growing services and innovations like Dash, an AI-powered knowledge management engine. The team operates with a startup mindset but builds for enterprise scale, focusing on reliability, speed, and scalability across global data centers.

Virtual First at Dropbox

Dropbox's Virtual First model prioritizes flexibility, autonomy, and connection. Teams work remotely with core collaboration hours, focusing on asynchronous communication to reduce meetings and respect deep work. Intentional in-person connections are facilitated through team gatherings, on-demand workspaces, and Neighborhood events. This model ensures equal access to opportunity, growth, and impact for all employees, regardless of location. This role requires approximately 5-10% travel for offsites and team gatherings.

Key skills/competency

• Data Engineering
• Analytics Engineering
• SQL (Spark SQL)
• Python Development
• Dimensional Modeling
• Data Architecture
• Airflow
• dbt
• Data Governance
• CI/CD Workflows
• Lakehouse Architecture
• Observability Tools
• Metrics Layer
• Cross-functional Alignment
• AI-native Tooling